python-3.x - 如何在直方图上获得最佳高斯拟合

Question

我有一个直方图，我正在尝试拟合最佳范数（高斯）函数，如下所示。问题是高斯拟合并不是我预期的最佳拟合。

import matplotlib.pyplot as plt
import numpy as np
import matplotlib.mlab as mlab
from astropy.modeling import models, fitting

bins=np.arange(-1,8,0.3)
#Reading data

a18 = np.loadtxt('AndXII18I.srt')
arr18 = np.array(a18[:,11])
axs[0,0].hist(arr18,bins,histtype='step')
axs[0,0].set_xlim([np.min(arr18), np.max(arr18)])

x = np.linspace(-1, bins[len(bins)-2],len(bins)-1)
x1 = np.linspace(-1, 8, 1000)

# guesses for the parameters:
g_init = models.Gaussian1D(1, 0, 1.)
fit_g = fitting.LevMarLSQFitter()

axs[0,0].plot(x1,t18)
axs[0,0].plot(edges18[8],hist18[8],'o')
g18 = fit_g(g_init, x, y18[0])
a18=g18.mean
t18=g18.amplitude*np.exp(-(x1-a18)**2/(2*g18.stddev**2))

plt.show()

标签： python-3.x